Various exports from Brown Corpus and useful scripts.

Corpus Linguistics slides, labs, assignments and data

Sentence generator using tokens from the Brown corpus

Part-Of-Speech-tagging using Hidden Markov model to identify the category of words ('noun', 'verb', ...) in plain text.

POS tagging using a Hidden Markov Model (HMM) with Viterbi Decoding

Viterbi Algorithm for POS tagging of sentences using Brown corpus

A program which guesses next words based on the user's input. Suggestions are the words with the highest probability to follow what has been already written, calculated in the n_grams of different size.

Auto tagger created with RNN using Bi-LSTM cell

Simple Python Implementation of Stemmer and Lemmatizer

Quantify the similarity between pairs of words of a dataset using Lin similarity, NPMI and LSA.

Text Analysis techniques using Brown Corpus , CMU dictionary

This project trains a Long Short Term Memory (LSTM) network to detect and classify a text written in English according to a particular variant: whether it is British or American.

Natural Language Processing (2018)

An implementation of static word embedding techniques for natural language processing, featuring SVD, CBOW, and Skip-gram models.

This notebook explores how clustering semantically similar words can help make Natural Language Processing tasks easier.

Implemented a collection of Ngram language models on brown corpus from scratch

Hidden Markov Model for Part of Speech Tagging

Fun in-class exercise for understanding the inner workings of word2vec in NLP. Implemented Google News 300 word2vec pre-trained model, and also trained a model from scratch with an existing text dataset (Brown Corpus).